Ludovicus P. H. van Beek

Climate Change Will Affect the Asian Water Towers

Towering Figures The Tibetan plateau and adjacent mountain ranges are the source areas of the five major rivers of Asia. Climate change promises to affect both precipitation patterns and glacial melting in the region, which could have marked impacts on river flows and on associated agriculture. Immerzeel et al. (p. 1382) analyzed the relative importance of glacial meltwater and rainfall in the region in order to determine how the rivers depend on different sources of water, and how the river basins may be affected by climate change. Climate change is likely to affect water availability in the river basins in substantial but diverse ways, which may threaten the food security of tens of millions of people. Climate change will cause substantial but diverse changes in water availability in the major river basins of Southeast Asia. More than 1.4 billion people depend on water from the Indus, Ganges, Brahmaputra, Yangtze, and Yellow rivers. Upstream snow and ice reserves of these basins, important in sustaining seasonal water availability, are likely to be affected substantially by climate change, but to what extent is yet unclear. Here, we show that meltwater is extremely important in the Indus basin and important for the Brahmaputra basin, but plays only a modest role for the Ganges, Yangtze, and Yellow rivers. A huge difference also exists between basins in the extent to which climate change is predicted to affect water availability and food security. The Brahmaputra and Indus basins are most susceptible to reductions of flow, threatening the food security of an estimated 60 million people.

Water balance of global aquifers revealed by groundwater footprint

Groundwater is a life-sustaining resource that supplies water to billions of people, plays a central part in irrigated agriculture and influences the health of many ecosystems. Most assessments of global water resources have focused on surface water, but unsustainable depletion of groundwater has recently been documented on both regional and global scales. It remains unclear how the rate of global groundwater depletion compares to the rate of natural renewal and the supply needed to support ecosystems. Here we define the groundwater footprint (the area required to sustain groundwater use and groundwater-dependent ecosystem services) and show that humans are overexploiting groundwater in many large aquifers that are critical to agriculture, especially in Asia and North America. We estimate that the size of the global groundwater footprint is currently about 3.5 times the actual area of aquifers and that about 1.7 billion people live in areas where groundwater resources and/or groundwater-dependent ecosystems are under threat. That said, 80 per cent of aquifers have a groundwater footprint that is less than their area, meaning that the net global value is driven by a few heavily overexploited aquifers. The groundwater footprint is the first tool suitable for consistently evaluating the use, renewal and ecosystem requirements of groundwater at an aquifer scale. It can be combined with the water footprint and virtual water calculations, and be used to assess the potential for increasing agricultural yields with renewable groundwaterref. The method could be modified to evaluate other resources with renewal rates that are slow and spatially heterogeneous, such as fisheries, forestry or soil.

Human water consumption intensifies hydrological drought worldwide

Over the past 50 years, human water use has more than doubled and affected streamflow over various regions of the world. However, it remains unclear to what degree human water consumption intensifies hydrological drought (the occurrence of anomalously low streamflow). Here, we quantify over the period 1960‐2010 the impact of human water consumption on the intensity and frequency of hydrological drought worldwide. The results show that human water consumption substantially reduced local and downstream streamflow over Europe, North America and Asia, and subsequently intensified the magnitude of hydrological droughts by 10‐500%, occurring during nation- and continent-wide drought events. Also, human water consumption alone increased global drought frequency by 27 ( 6)%. The intensification of drought frequency is most severe over Asia (35 7%), but also substantial over North America (25 6%) and Europe (20 5%). Importantly, the severe drought conditions are driven primarily by human water consumption over many parts of these regions. Irrigation is responsible for the intensification of hydrological droughts over the western and central US, southern Europe and Asia, whereas the impact of industrial and households’ consumption on the intensification is considerably larger over the eastern US and western and central Europe. Our findings reveal that human water consumption is one of the more important mechanisms intensifying hydrological drought, and is likely to remain as a major factor affecting drought intensity and frequency in the coming decades.

High‐resolution modeling of human and climate impacts on global water resources

A number of global hydrological models [GHMs) have been developed in recent decades in order to understand the impacts of climate variability and human activities on water resources availability. The spatial resolution of GHMs is mostly constrained at a 0.5° by 0.5° grid [∼50km by ∼50km at the equator). However, for many of the water-related problems facing society, the current spatial scale of GHMs is insufficient to provide locally relevant information. Here using the PCR-GLOBWB model we present for the first time an analysis of human and climate impacts on global water resources at a 0.1° by 0.1° grid [∼10km by ∼10km at the equator) in order to depict more precisely regional variability in water availability and use. Most of the model input data (topography, vegetation, soil properties, routing, human water use) have been parameterized at a 0.1° global grid and feature a distinctively higher resolution. Distinct from many other GHMs, PCR-GLOBWB includes groundwater representation and simulates groundwater heads and lateral groundwater flows based on MODFLOW with existing geohydrological information. This study shows that global hydrological simulations at higher spatial resolutions are feasible for multi-decadal to century periods.

A physically-based model of global freshwater surface temperature

[1] Temperature determines a range of physical properties of water and exerts a strong control on surface water biogeochemistry. Thus, in freshwater ecosystems the thermal regime directly affects the geographical distribution of aquatic species through their growth and metabolism and indirectly through their tolerance to parasites and diseases. Models used to predict surface water temperature range between physically based deterministic models and statistical approaches. Here we present the initial results of a physically based deterministic model of global freshwater surface temperature. The model adds a surface water energy balance to river discharge modeled by the global hydrological model PCR-GLOBWB. In addition to advection of energy from direct precipitation, runoff, and lateral exchange along the drainage network, energy is exchanged between the water body and the atmosphere by shortwave and longwave radiation and sensible and latent heat fluxes. Also included are ice formation and its effect on heat storage and river hydraulics. We use the coupled surface water and energy balance model to simulate global freshwater surface temperature at daily time steps with a spatial resolution of 0.5 � on a regular grid for the period 1976–2000. We opt to parameterize the model with globally available data and apply it without calibration in order to preserve its physical basis with the outlook of evaluating the effects of atmospheric warming on freshwater surface temperature. We validate our simulation results with daily temperature data from rivers and lakes (U.S. Geological Survey (USGS), limited to the USA) and compare mean monthly temperatures with those recorded in the Global Environment Monitoring System (GEMS) data set. Results show that the model is able to capture the mean monthly surface temperature for the majority of the GEMS stations, while the interannual variability as derived from the USGS and NOAA data was captured reasonably well. Results are poorest for the Arctic rivers because the timing of ice breakup is predicted too late in the year due to the lack of including a mechanical breakup mechanism. Moreover, surface water temperatures for tropical rivers were overestimated, most likely due to an overestimation of rainfall temperature and incoming shortwave radiation. The spatiotemporal variation of water temperature reveals large temperature differences between water and atmosphere for the higher latitudes, while considerable lateral transport of heat can be observed for rivers crossing hydroclimatic zones, such as the Nile, the Mississippi, and the large rivers flowing to the Arctic. Overall, our model results show promise for future projection of global surface freshwater temperature under global change.

Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data

Significance We increasingly rely on global models to project impacts of humans and climate on water resources. How reliable are these models? While past model intercomparison projects focused on water fluxes, we provide here the first comprehensive comparison of land total water storage trends from seven global models to trends from Gravity Recovery and Climate Experiment (GRACE) satellites, which have been likened to giant weighing scales in the sky. The models underestimate the large decadal (2002–2014) trends in water storage relative to GRACE satellites, both decreasing trends related to human intervention and climate and increasing trends related primarily to climate variations. The poor agreement between models and GRACE underscores the challenges remaining for global models to capture human or climate impacts on global water storage trends. Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002–2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤−0.5 km3/y) and increasing (≥0.5 km3/y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km3/y, whereas most models estimate decreasing trends (−71 to 11 km3/y). Land water storage trends, summed over all basins, are positive for GRACE (∼71–82 km3/y) but negative for models (−450 to −12 km3/y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated.

Linking groundwater use and stress to specific crops using the groundwater footprint in the Central Valley and High Plains aquifer systems, U.S.

A number of aquifers worldwide are being depleted, mainly by agricultural activities, yet groundwater stress has not been explicitly linked to specific agricultural crops. Using the newly developed concept of the groundwater footprint (the area required to sustain groundwater use and groundwater-dependent ecosystem services), we develop a methodology to derive crop-specific groundwater footprints. We illustrate this method by calculating high-resolution groundwater footprint estimates of crops in two heavily used aquifer systems: the Central Valley and High Plains, U.S. In both aquifer systems, hay and haylage, corn, and cotton have the largest groundwater footprints, which highlights that most of the groundwater stress is induced by crops meant for cattle feed. Our results are coherent with other studies in the High Plains but suggest lower groundwater stress in the Central Valley, likely due to artificial recharge from surface water diversions which were not taken into account in previous estimates. Uncertainties of recharge and irrigation application efficiency contribute the most to the total relative uncertainty of the groundwater footprint to aquifer area ratios. Our results and methodology will be useful for hydrologists, water resource managers, and policy makers concerned with which crops are causing the well-documented groundwater stress in semiarid to arid agricultural regions around the world.

From scripts towards provenance inference

Scientists require provenance information either to validate their model or to investigate the origin of an unexpected value. However, they do not maintain any provenance information and even designing the processing workflow is rare in practice. Therefore, in this paper, we propose a solution that can build the workflow provenance graph by interpreting the scripts used for actual processing. Further, scientists can request fine-grained provenance information facilitating the inferred workflow provenance. We also provide a guideline to customize the workflow provenance graph based on user preferences. Our evaluation shows that the proposed approach is relevant and suitable for scientists to manage provenance.

Exploring spatiotemporal changes of the Yangtze River (Changjiang) nitrogen and phosphorus sources, retention and export to the East China Sea and Yellow Sea

Nitrogen (N) and phosphorus (P) flows from land to sea in the Yangtze River basin were simulated for the period 1900-2010, by combining models for hydrology, nutrient input to surface water, and an in-stream retention. This study reveals that the basin-wide nutrient budget, delivery to surface water, and in-stream retention increased during this period. Since 2004, the Three Gorges Reservoir has contributed 5% and 7% of N and P basin-wide retention, respectively. With the dramatic rise in nutrient delivery, even this additional retention was insufficient to prevent an increase of riverine export from 337 Gg N yr-1 and 58 Gg P yr-1 (N:P molar ratio = 13) to 5896 Gg N yr-1 and 381 Gg P yr-1 (N:P molar ratio = 35) to the East China Sea and Yellow Sea (ECSYS). The midstream and upstream subbasins dominate the N and P exports to the ECSYS, respectively, due to various human activities along the river. Our spatially explicit nutrient source allocation can aid in the strategic targeting of nutrient reduction policies. We posit that these should focus on improving the agricultural fertilizer and manure use efficiency in the upstream and midstream and better urban wastewater management in the downstream subbasin.